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Model: GELU Model: 4 Layers, 2048 Neurons per Layer

Dataset: 80% C4 (Web Text) and 20% Python Code

Neuron 612 in Layer 1

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Transformer Lens Loading: HookedTransformer.from_pretrained('gelu-4l')



Text #0

Max Range: 3.8017. Min Range: -3.8017

Max Act: 3.8017. Min Act: -0.1700

Data Index: 1262050 (C4 (Web Text))

Max Activating Token Index: 769

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Text #1

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Max Act: 3.7078. Min Act: -0.1700

Data Index: 595699 (C4 (Web Text))

Max Activating Token Index: 305

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Text #2

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Max Act: 3.7391. Min Act: -0.1700

Data Index: 1199161 (C4 (Web Text))

Max Activating Token Index: 723

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Text #3

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Max Act: 3.6139. Min Act: -0.1700

Data Index: 335046 (C4 (Web Text))

Max Activating Token Index: 492

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Text #4

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Max Act: 3.6452. Min Act: -0.1700

Data Index: 447235 (C4 (Web Text))

Max Activating Token Index: 732

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Text #5

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Data Index: 181041 (C4 (Web Text))

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Text #6

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Data Index: 89618 (C4 (Web Text))

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Text #7

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Data Index: 295593 (C4 (Web Text))

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Text #8

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Max Act: 3.6139. Min Act: -0.1700

Data Index: 394608 (C4 (Web Text))

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Text #9

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Data Index: 1037435 (C4 (Web Text))

Max Activating Token Index: 755

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Text #10

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Data Index: 1554838 (Python Code)

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Text #11

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Text #12

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Data Index: 910621 (C4 (Web Text))

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Text #13

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Data Index: 485460 (C4 (Web Text))

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Text #14

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Text #15

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Data Index: 1637935 (Python Code)

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Text #16

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Data Index: 1283754 (C4 (Web Text))

Max Activating Token Index: 968

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Text #17

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Data Index: 192748 (C4 (Web Text))

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Text #18

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Data Index: 1227043 (C4 (Web Text))

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Text #19

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Data Index: 1583922 (Python Code)

Max Activating Token Index: 53

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